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		<title>Sun et al 2018a - Revision history</title>
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		<updated>2026-05-01T02:41:42Z</updated>
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		<title>Scipediacontent: Scipediacontent moved page Draft Content 664639800 to Sun et al 2018a</title>
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				<updated>2021-01-28T23:30:13Z</updated>
		
		<summary type="html">&lt;p&gt;Scipediacontent moved page &lt;a href=&quot;/public/Draft_Content_664639800&quot; class=&quot;mw-redirect&quot; title=&quot;Draft Content 664639800&quot;&gt;Draft Content 664639800&lt;/a&gt; to &lt;a href=&quot;/public/Sun_et_al_2018a&quot; title=&quot;Sun et al 2018a&quot;&gt;Sun et al 2018a&lt;/a&gt;&lt;/p&gt;
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				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;Revision as of 23:30, 28 January 2021&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan='2' style='text-align: center;' lang='en'&gt;&lt;div class=&quot;mw-diff-empty&quot;&gt;(No difference)&lt;/div&gt;
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		<author><name>Scipediacontent</name></author>	</entry>

	<entry>
		<id>https://www.scipedia.com/wd/index.php?title=Sun_et_al_2018a&amp;diff=195753&amp;oldid=prev</id>
		<title>Scipediacontent: Created page with &quot; == Abstract ==  Rain removal aims to remove the rain streaks on rain images. The state-of-the-art methods are mostly based on Convolutional Neural Network~(CNN). However, as...&quot;</title>
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				<updated>2021-01-28T23:30:08Z</updated>
		
		<summary type="html">&lt;p&gt;Created page with &amp;quot; == Abstract ==  Rain removal aims to remove the rain streaks on rain images. The state-of-the-art methods are mostly based on Convolutional Neural Network~(CNN). However, as...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
Rain removal aims to remove the rain streaks on rain images. The state-of-the-art methods are mostly based on Convolutional Neural Network~(CNN). However, as CNN is not equivariant to object rotation, these methods are unsuitable for dealing with the tilted rain streaks. To tackle this problem, we propose Deep Symmetry Enhanced Network~(DSEN) that is able to explicitly extract the rotation equivariant features from rain images. In addition, we design a self-refining mechanism to remove the accumulated rain streaks in a coarse-to-fine manner. This mechanism reuses DSEN with a novel information link which passes the gradient flow to the higher stages. Extensive experiments on both synthetic and real-world rain images show that our self-refining DSEN yields the top performance.&lt;br /&gt;
&lt;br /&gt;
Comment: Accepted by ICIP 19. Corresponding author: Hanrong Ye&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Original document ==&lt;br /&gt;
&lt;br /&gt;
The different versions of the original document can be found in:&lt;br /&gt;
&lt;br /&gt;
* [http://arxiv.org/abs/1811.04761 http://arxiv.org/abs/1811.04761]&lt;br /&gt;
&lt;br /&gt;
* [https://ink.library.smu.edu.sg/sis_research/4449 https://ink.library.smu.edu.sg/sis_research/4449] under the license cc-by-nc-nd&lt;br /&gt;
&lt;br /&gt;
* [http://xplorestaging.ieee.org/ielx7/8791230/8799366/08803265.pdf?arnumber=8803265 http://xplorestaging.ieee.org/ielx7/8791230/8799366/08803265.pdf?arnumber=8803265],&lt;br /&gt;
: [http://dx.doi.org/10.1109/icip.2019.8803265 http://dx.doi.org/10.1109/icip.2019.8803265]&lt;br /&gt;
&lt;br /&gt;
* [https://dblp.uni-trier.de/db/conf/icip/icip2019.html#0008YLSLS19 https://dblp.uni-trier.de/db/conf/icip/icip2019.html#0008YLSLS19],&lt;br /&gt;
: [https://ink.library.smu.edu.sg/sis_research/4449 https://ink.library.smu.edu.sg/sis_research/4449],&lt;br /&gt;
: [https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=5452&amp;amp;context=sis_research https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=5452&amp;amp;context=sis_research],&lt;br /&gt;
: [https://academic.microsoft.com/#/detail/2970543065 https://academic.microsoft.com/#/detail/2970543065]&lt;/div&gt;</summary>
		<author><name>Scipediacontent</name></author>	</entry>

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